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© 2014 IEEE. This paper presents research that investigated the effects of mental fatigue on brain activity using electroencephalogram (EEG) signals. Since EEG signals are considered to be non-stationary, time-frequency analysis has frequently been used for analysis. The S-transform is a time-frequency analysis method and is used in this paper to analyze EEG signals during alert and fatigue states during a driving simulator task. Repeated-measure MANOVA results show significant differences between alert and fatigue states within the alpha (8-13Hz) frequency band. The two sites demonstrating the greatest increases in alpha activity during fatigue were the Cz and P4 sites. The results show that S-transform analysis can be used to distinguish between alert and fatigue states in the EEG and also supports the use of the S-transform for EEG analysis.

This investigation examined the impact of spinal cord injury (SCI) on task-relevant processing using event-related potentials. Thirty-seven participants with chronic SCI and 37 healthy able-bodied controls were tested in this study. An auditory two-tone button press oddball discrimination paradigm was used to evoke the N100, P200, N200, and P300 components of the event-related potential. During the early sensory/perceptual stages of target stimulus processing, the SCI group showed an earlier right posterior P200 latency relative to the controls. In the later more cognitive stages, a pattern of diminished left and right posterior P300 amplitude was also evident. This was further coupled with increased false-positive errors and greater variability of response time in the SCI group. The results of this study indicate that people with SCI show disturbances in inhibitory function and alterations in both early perceptual encoding processes and in later executive functioning that engages contextual/memory-updating operations. Copyright © 2013 by the American Clinical Neurophysiology Society.

Assessing brain wave activity is a viable strategy for monitoring fatigue when performing tasks such as driving, and numerous studies have been conducted in this area. However, results of a systematic review on changes in brain wave activity associated with fatigue have revealed equivocal findings. This study investigated brain wave activity associated with fatigue in 48 nonprofessional healthy drivers as they participated in a simulated driving task until they fatigued. The results showed that as a person fatigues, slow wave activity increased over the entire cortex, in theta and in alpha 1 and 2 bands, while no significant changes were found in delta wave activity. Substantial increases also occurred in fast wave activity, though mostly in frontal sites. The results suggest that as a person fatigues, the brain loses capacity and slows its activity, and that attempts to maintain vigilance levels lead to increased beta activity. © 2012 Society for Psychophysiological Research.

Objective: To study the impact of fatigue on health-related quality of life (HR-QOL) associated with spinal cord injury (SCI). Design: Matched group design with several independent measures. Setting: University-based laboratory. Participants: Persons with SCI (n=41) and an average 16.5 years duration of community living with SCI and a group of able-bodied controls (n=41) with similar sex ratio, age, and level of education. Participants with SCI were enrolled through rehabilitation unit contacts and through advertising in newsletters. Interventions: Not applicable. Main Outcome Measures: The main independent measures reported in this article include the Iowa Fatigue Scale and the Medical Outcomes Study 36-Item Short-Form Health Survey. Results: As expected, persons with SCI were found to have significantly lower HR-QOL. Fatigue was found to be more prevalent in the SCI group, and was associated with lower HR-QOL in both groups. Factorial analysis of variance indicated significant interactions in which persons with SCI with low fatigue levels had similar HR-QOL to the able-bodied controls regardless of their fatigue level, while persons with SCI with elevated fatigue had significantly reduced HR-QOL. Factors such as age, education, completeness and level of lesion, and community integration were not associated with increased fatigue levels. However, a shorter time since injury was found to be significantly associated with higher levels of fatigue. Conclusions: The Iowa Fatigue Scale data suggest over 50% of the SCI group had elevated fatigue, which was associated with significantly reduced HR-QOL. Research is needed that identifies factors that raise vulnerability to fatigue, and strategies designed to address the negative impacts of fatigue need to be evaluated. © 2012 American Congress of Rehabilitation Medicine.

This study investigated fatigue and anger in people with SCI. Participants were 27 adults with SCI living in the community (males = 26, females = 1; mean age = 50 years, SD = 9.47 years) and a comparison group of 27 other adults without SCI. Data about their experience of fatigue and anger were collected using the Chalder Fatigue Scale and the Profile of Mood States. Kruskal-Wallis ANOVA by ranks and chi-square analyses were used to determine whether the SCI participants had elevated levels of fatigue and anger than the typical or noninjured community group. Persons with SCI reported significantly elevated fatigue and elevated levels of anger than typical others. These findings are discussed with reference to adjustment following SCI, and interpreted in light of the Stress Appraisal and Coping Model (SAC) of adjustment following SCI. © 2012, Cambridge University Press. All rights reserved.

This paper presents research that investigated the effects of mental fatigue on brain activity associated with eyes open and eyes closed conditions. The changes associated with electroencephalography (EEG) alpha wave activity (8-13Hz) during eye closure has previously been shown to be an effective strategy for switching and activating devices as an environmental control system (ECS) designed for people with severe disability like spinal cord injury (SCI). The results showed that switching times did increase due to fatigue, however, these increases were not large (around 1 second longer to switch) and this difference was not significant. When baselines were readjusted taking into account the change in alpha wave activity due to the fatigue, switching reduced to times typically seen when the person was alert. Error rates were similar between the alert and fatigue sates. Implications of these results for a hands-free ECS are discussed. © 2011 IEEE.

Driver fatigue is known to be a major risk factor for road and work-related accidents that can often result in serious injury or death. However, despite the obvious need to investigate factors that may contribute to this problem, there still remains considerable uncertainty and debate concerning determinants of driver related fatigue. In other words, factors that contribute to a person fatiguing when they perform a sensor-motor task like driving a motor vehicle over an extended period of time. This chapter discusses definitions of driver fatigue, possible symptoms, and the contribution of psychophysiological factors. The chapter will also present findings from a driver simulator study that investigated both physiological and psychological determinants of fatigue. It involved three outcome measures, including a physiological, psychological and a combined physiological and psychological measure. Participants included 50 male and female adults who held a current drivers license. All subjects performed a driving simulator task till they exhibited symptoms of fatigue in a temperature controlled laboratory. They were assessed immediately before and after the simulated driving task, as well as throughout the driving task, using a comprehensive assessment regimen including general health, brain wave activity, heart rate variability, respiration, eye blink activity, peripheral skin temperature, and psychological measures of personality, fatigue and mood states. Significant predictors for the physiological fatigue measure included higher levels of delta activity and low levels of liveliness and self-sufficiency. Determinants for the psychological fatigue outcome measure included anxiety, low levels of vigor and low levels of self-sufficiency. The combined fatigue outcome measure was determined by factors such as anxiety, low levels of self-sufficiency and high levels of theta activity. These results are believed to support a two-level processing model of fatigue. The findings

Fatigue can be defined as a state that involves psychological and physical tiredness with a range of symptoms such as tired eyes, yawning and increased blink rate. It has major implications for work place and road safety as well as a negative symptom of many acute and chronic illnesses. As such there has been considerable research dedicated to systems or algorithms that can be used to detect and monitor the onset of fatigue. This paper examines using electroencephalography (EEG) signals to classify fatigue and alert states as a function of subjective self-report, driving performance and physiological symptoms. The results show that EEG classification network for fatigue improved from 75% to 80% when these factors are applied, especially when the data is grouped by subjective selfreport of fatigue with classification accuracy improving to 84.5%. © 2010 IEEE.

Fatigue is a prevalent problem in the workplace and a common symptom of many diseases. However, its relationship with the autonomic nervous system, specifically with sympathetic arousal, needs clarification. The objective of this study was to determine the association between fatigue and heart rate variability (HRV). HRV is regarded as an indicator of the autonomic regulation activity of heart rate, specifically sympathetic and parasympathetic activity. Spectral changes in low-frequency (LF; 0.04-0.15 Hz) and high-frequency (HF; 0.15-0.4 Hz) components of HRV have been reported to be associated with distressing conditions such as hemorrhagic shock, acute myocardial infarction, elevated anxiety, and depressed mood. While HRV changes have been found in persons with chronic fatigue syndrome, its association with fatigue in healthy individuals still needs clarification. HRV was assessed in a total of 50 participants who were asked to perform a task until becoming fatigued. Low-frequency HRV activity increased, while indices of parasympathetic modulation such as RMSSD and pNN50 remained stable as participants experienced fatigue, suggesting that fatigue in healthy individuals may be associated with increased sympathetic arousal. In addition, employing multiple regression analyses, we could positively associate the change in LF/HF HRV ratio from baseline to fatigue with factors such as emotional stability, warmth and tension and negatively associate it with social boldness and self-reported levels of vigor. © 2009 Federation of European Psychophysiology Societies.

Fatigue is a negative symptom of many illnesses and also has major implications for road safety. This paper presents results using a method called microstate segmentation (MSS). It was used to distinguish changes from an alert to a fatigue state. The results show a significant increase in MSS instantaneous amplitude during the fatigue state. Plotting the linear gradient of the nonlinear part of the phase data from the MSS also showed a significant difference (P<0.01) in the gradients of the alert state compared to the fatigue state. The results suggest that MSS can be used in analyzing spontaneous electroencephalography (EEG) signals to detect changes in physiological states. The results have implications for countermeasures used in detecting fatigue. ©2009 IEEE.

Brain computer interfaces (BCIs) can be implemented into assistive technologies to provide 'hands-free' control for the severely disabled. BCIs utilise voluntary changes in one's brain activity as a control mechanism to control devices in the person's immediate environment. Performance of BCIs could be adversely affected by negative physiological conditions such as fatigue and altered electrophysiology commonly seen in spinal cord injury (SCI). This study examined the effects of mental fatigue from an increase in cognitive demand on the brain activity of those with SCI. Results show a trend of increased alpha (8-13Hz) activity in able-bodied controls after completing a set of cognitive tasks. Conversely, the SCI group showed a decrease in alpha activity due to mental fatigue. Results suggest that the brain activity of SCI persons are altered in its mechanism to adjust to mental fatigue. These altered brain conditions need to be addressed when using BCIs in clinical populations such as SCI. The findings have implications for the improvement of BCI technology.

Research and development has been conducted on a "hands-free" brain wave activity (electroencephalography-based) assistive technology device called the Mind Switch. It has been designed to provide a severely disabled person (such as someone with tetraplegia) with the ability to switch using their brain activity and thus activate devices in the environment. An area of concern has been the time it takes to complete set-up of the system before individual use, as well as the occurrence of errors in switching rates. In order to improve the user friendliness of the system, this study compared the efficacy of detecting electroencephalography (EEG) changes in brain signals that occur with eye closure and used as a "switch", with two different methods of processing the EEG. Using data from spinal cord injured participants, fractal analysis, that is, the change in fractal dimension of the EEG wave during eye closure was compared to the original method of using spectral analysis change. In comparison to the spectral technique, the fractal dimension technique improved set up time, and was substantially improved in reducing the number of false positive and false negative errors when activating the device. Furthermore, the time to switch was also marginally reduced when using fractal dimension processing. Implications for improving the viability of an EEG based environmental control system for the severely neurologically injured are discussed. © 2008 IOS Press. All rights reserved.

Brain computer interface (BCI) technology as Its name implies, relies upon decoding brain signals into operational commands. Aside from needing effective means of control, successful BCIs need to remain stable in varying physiological conditions. BCIs need to be developed with mechanisms to recognise and respond to physiological states (such as stress and fatigue) that can disrupt user capability. This paper compares a spectral analysis of EEG signals technique with a nonlinear method of sample entropy to detect changes In brain dynamics during moments of stress and fatigue. The results demonstrated few changes In the spectral frequency bands of the EEG during fatigue and stress conditions. However, when the EEG signals were analysed with the nonlinear technique of sample entropy the results indicated a reduction of complexity during moments of fatigue and stress and an increase In complexity during moments of engagement to the task. © 2007 IEEE.

Driver fatigue is a major risk for road accidents that can often result in injury and death. However, considerable debate still exists concerning factors associated with driver fatigue. Because of the complex nature of fatigue, this paper reports a study that investigated both physiological and psychological determinants of fatigue. Three fatigue outcome measures were used, including a physiological, psychological and a combined physiological and psychological measure. Fifty participants performed a driving simulator task till they showed symptoms of fatigue and were assessed before and after the task. Significant factors associated with physiological fatigue included higher levels of baseline delta activity and an extraverted personality. Factors related to the psychological fatigue outcome measure included sleepiness, low healthy lifestyle status, an extraverted personality and tension-prone personality, and negative mood states. The combined fatigue outcome measure was associated with factors such as a tension-prone and extraverted personality, low systolic blood pressure, and negative mood states. The findings emphasize the importance of assessing fatigue using a range of outcome measures in order to achieve a thorough understanding of what factors contribute to fatigue and highlight the need to develop fatigue countermeasures that employ a broad range of measures. © 2006 Elsevier B.V. All rights reserved.

Driver fatigue is associated with risks of road accidents that result in injury and death. Research has been limited by several issues such as confusion over definitions, how best to measure fatigue, and the contribution of psychological factors to fatigue. This study addressed these limitations by investigating the relationship between psychological factors and fatigue. Participants were assessed and were required to perform a monotonous task till they tired. Results found few psychological factors to be related to physiological and performance decrement fatigue outcome measures. However, psychological factors were found to correlate consistently with self-reported fatigue. The results suggest that fatigue is associated with a predisposition to be anxious, depressive, less self-assured, more conscientious (rule bound), less socially bold, less adaptable and low vigour. The results indicate that future research should employ a range of fatigue outcome measures in order to best understand what factors contribute to fatigue. © 2005 Elsevier B.V. All rights reserved.